The present invention generally relates to assigning and reporting the cleanliness of objects and areas, and particularly relates to utilization of object and area cleanliness states as determined by the opposing processes of cleaning and dirtying detected through various methods to provide an indication of the state of cleanliness potentially utilized to alter the process of cleaning and/or dirtying to reach a desired state of cleanliness. Detection of the cleaning and dirtying operations can be performed automatically through image processing and behavior detection of still images/video indicating the activity taking place in the area of interest and time. The state of cleanliness can then be reported to interested parties as textual reports and/or augmented reality overlays on still images/video.
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2. The cleanliness monitoring system of claim 1, wherein the processing circuitry is configured to output the indication of the value of the cleanliness estimate as video overlay information, for overlaying a video or still image of the physical object or area.
This invention relates to a cleanliness monitoring system designed to assess and display the cleanliness of physical objects or areas. The system addresses the challenge of visually communicating cleanliness levels in real-time, which is critical in environments where hygiene is paramount, such as healthcare, food processing, or manufacturing. The system includes sensors that detect contaminants or cleanliness markers on a surface, processing circuitry that analyzes the sensor data to generate a cleanliness estimate, and an output mechanism that conveys this estimate. The processing circuitry is configured to display the cleanliness estimate as a video overlay, superimposing the cleanliness information directly onto a live or recorded video feed or still image of the monitored object or area. This overlay ensures that users can immediately see the cleanliness status in context, enhancing situational awareness and decision-making. The system may also include additional features, such as adjustable thresholds for cleanliness levels, historical tracking of cleanliness data, and alerts for when cleanliness falls below acceptable standards. The overlay can be customized to highlight specific regions of interest or to display numerical or color-coded cleanliness scores. By integrating cleanliness assessment with visual feedback, the system improves efficiency and accuracy in maintaining hygiene standards.
3. The cleanliness monitoring system of claim 2, wherein the video overlay information comprises a color-coded graphical overlay, wherein the color of the color-coded graphical overlay indicates the value of the cleanliness estimate and wherein the processing circuitry is configured to change the color of the color-coded graphical overlay responsive to changing the value of the cleanliness estimate.
A cleanliness monitoring system is designed to assess and visually indicate the cleanliness of a surface or environment in real time. The system captures video or image data of the target area and processes this data to generate a cleanliness estimate, which quantifies the level of cleanliness based on detected contaminants, debris, or other relevant factors. The system then overlays this information onto the captured video or image data as a color-coded graphical overlay. The color of the overlay dynamically changes in response to variations in the cleanliness estimate, providing an intuitive visual representation of cleanliness levels. For example, a green overlay may indicate a high level of cleanliness, while a red overlay may signal poor cleanliness. This visual feedback allows users to quickly assess and monitor cleanliness without requiring detailed numerical analysis. The system may also include additional processing circuitry to adjust the overlay based on real-time changes in the cleanliness estimate, ensuring continuous and accurate monitoring. This technology is particularly useful in environments where cleanliness is critical, such as medical facilities, food processing plants, or manufacturing settings.
4. The cleanliness monitoring system of claim 1, wherein the processing circuitry is configured to output the indication of the value of the cleanliness estimate in one or more textual reports generated by the cleanliness monitoring system.
A cleanliness monitoring system is designed to assess and report the cleanliness of a monitored environment, such as a cleanroom or manufacturing facility. The system addresses the need for accurate, real-time monitoring of contamination levels to ensure compliance with hygiene standards and operational requirements. The system includes sensors that detect particulate matter or other contaminants in the environment, and processing circuitry that analyzes the sensor data to generate a cleanliness estimate. This estimate quantifies the level of contamination present, allowing operators to assess environmental conditions. The system further includes a reporting feature that outputs the cleanliness estimate in one or more textual reports. These reports provide a clear, documented record of the cleanliness levels over time, enabling trend analysis, compliance verification, and corrective actions. The reports may be generated periodically or on demand, depending on system configuration. This feature ensures that cleanliness data is easily accessible and actionable, supporting decision-making and process optimization in environments where contamination control is critical. The system may also include additional functionalities, such as alerts for threshold breaches or integration with other monitoring systems, to enhance its utility in maintaining cleanliness standards.
5. The cleanliness monitoring system of claim 1, wherein the initial value corresponds to a cleanest condition of the physical object or area, according to a defined range of values or a defined set of values ranging from cleanest to dirtiest.
A cleanliness monitoring system is designed to track and assess the cleanliness of a physical object or area over time. The system includes a sensor that measures a parameter indicative of cleanliness, such as dirt, dust, or contamination levels. The sensor generates a signal that is processed to determine a cleanliness value. This value is compared to an initial value, which represents the cleanest possible condition of the object or area within a predefined range or set of values that spans from cleanest to dirtiest. The system may also include a display or alert mechanism to indicate when the cleanliness value deviates from the initial value, signaling a need for cleaning or maintenance. The system may be used in environments where cleanliness is critical, such as medical facilities, food processing plants, or manufacturing settings, to ensure compliance with hygiene standards. The initial value serves as a baseline for comparison, allowing the system to detect deviations from optimal cleanliness levels and trigger appropriate actions.
6. The cleanliness monitoring system of claim 1, wherein, for at least one event type, the processing circuitry is configured to change the value of the cleanliness estimate further in dependence on an event duration or level of activity determined for each detected event of the at least one event type.
This invention relates to cleanliness monitoring systems designed to assess and track the cleanliness of environments, such as industrial or medical settings, where contamination control is critical. The system addresses the challenge of accurately estimating cleanliness by dynamically adjusting cleanliness estimates based on detected events and their characteristics. The system includes processing circuitry that monitors events affecting cleanliness, such as contamination incidents, cleaning activities, or environmental changes. For at least one type of event, the circuitry modifies the cleanliness estimate by considering the duration of the event or the level of activity associated with it. For example, a longer contamination event or a higher-intensity cleaning activity would result in a more significant adjustment to the cleanliness estimate compared to shorter or less intense events. This approach ensures that the cleanliness assessment reflects not just the occurrence of events but also their severity or impact. The system may also incorporate additional features, such as event detection mechanisms, data logging, and user interfaces for displaying cleanliness trends. By dynamically weighting events based on their duration or activity level, the system provides a more precise and context-aware cleanliness assessment, improving decision-making for maintenance and contamination control.
7. The cleanliness monitoring system of claim 1, wherein the processing circuitry is configured to set the value of the cleanliness estimate to the initial value or other predetermined value, in response to detecting events of the cleaning type.
The cleanliness monitoring system is designed to track and assess the cleanliness of a monitored area, such as a room or surface, by generating a cleanliness estimate. The system includes sensors that detect environmental conditions or events related to cleanliness, such as the presence of contaminants, cleaning activities, or user interactions. Processing circuitry analyzes the sensor data to generate a cleanliness estimate, which is a numerical or qualitative representation of the current cleanliness level. The system is configured to adjust the cleanliness estimate in response to detected events. Specifically, when the system detects events classified as cleaning-type events—such as the activation of a cleaning device, manual cleaning actions, or scheduled cleaning routines—the processing circuitry resets the cleanliness estimate to an initial value or another predetermined value. This ensures that the cleanliness estimate accurately reflects the state after cleaning, providing a reliable and up-to-date assessment. The system may also incorporate additional factors, such as time elapsed since the last cleaning event or sensor readings, to refine the cleanliness estimate over time. The goal is to provide an automated and objective measure of cleanliness, reducing the need for manual inspections and improving maintenance efficiency.
9. The cleanliness monitoring system of claim 8, wherein the processing circuitry is configured to receive the video images via the interface circuitry and to perform the video analysis to obtain the processed data.
The cleanliness monitoring system is designed for automated inspection of surfaces to detect and assess contamination. The system addresses the challenge of maintaining cleanliness in environments where contamination can impact product quality, safety, or operational efficiency, such as in manufacturing, healthcare, or food processing. Traditional manual inspection methods are time-consuming, subjective, and prone to human error, making automated solutions necessary for consistent and reliable monitoring. The system includes a camera or imaging device that captures video images of the target surface. These images are transmitted to processing circuitry via interface circuitry, which may include wired or wireless communication modules. The processing circuitry analyzes the video images to detect and quantify contamination, such as dust, debris, or stains, using image processing algorithms. The processed data may include metrics like contamination area, density, or distribution, which are then used to generate cleanliness reports or trigger alerts if thresholds are exceeded. The system may also integrate with external databases or control systems to log results or initiate cleaning procedures. The processing circuitry is configured to handle the video data efficiently, ensuring real-time or near-real-time analysis. The system may further include calibration features to account for lighting conditions or surface variations, improving accuracy. By automating the inspection process, the system enhances efficiency, reduces human intervention, and ensures consistent cleanliness standards.
10. The cleanliness monitoring system of claim 8, wherein the processing circuitry is configured to receive the processed data via the interface circuitry, the processed data provided by an associated video analytics system that receives the video images and performs the video analysis.
A cleanliness monitoring system is designed to assess and track the cleanliness of surfaces, environments, or objects in real-time using video analysis. The system addresses the challenge of manually inspecting cleanliness, which is time-consuming, subjective, and prone to human error. By automating the process, it ensures consistent and objective cleanliness assessments, improving efficiency and reliability in environments such as hospitals, food processing facilities, or manufacturing plants. The system includes processing circuitry that receives processed data from an associated video analytics system. The video analytics system captures video images of the target area and performs analysis to detect and quantify cleanliness-related parameters, such as dirt, stains, or debris. The processed data, which may include cleanliness scores, contamination levels, or other relevant metrics, is then transmitted to the cleanliness monitoring system via interface circuitry. The processing circuitry further analyzes this data to generate reports, alerts, or control signals for corrective actions. This integration allows for seamless and automated cleanliness monitoring, reducing the need for manual inspections and enhancing overall hygiene management. The system can be configured to operate continuously or at scheduled intervals, ensuring ongoing compliance with cleanliness standards.
11. The cleanliness monitoring system of claim 8, wherein, for changing the value of the cleanliness estimate according to the classification, the processing circuitry is configured to change the value of the cleanliness estimate in a direction that corresponds to a dirtier condition of the physical object or area, in response to the recognized activity being classified as a dirtying activity.
The cleanliness monitoring system is designed to assess and track the cleanliness of physical objects or areas by analyzing detected activities. The system addresses the challenge of accurately monitoring cleanliness in environments where activities can either maintain or degrade cleanliness levels. The system includes sensors to detect activities and processing circuitry to classify these activities as either cleaning or dirtying activities. When an activity is classified as a dirtying activity, the system adjusts the cleanliness estimate in a direction that indicates a dirtier condition. This adjustment reflects the negative impact of the activity on cleanliness. The system may also include a user interface to display the cleanliness estimate and alerts when the cleanliness level falls below a predefined threshold. The processing circuitry may further analyze historical data to refine the cleanliness estimate over time. The system ensures real-time monitoring and proactive management of cleanliness in various environments, such as healthcare facilities, food processing plants, or residential spaces.
12. The cleanliness monitoring system of claim 8, wherein, for changing the value of the cleanliness estimate according to the classification, the processing circuitry is configured to change the value of the cleanliness estimate in a direction that corresponds to a cleaner condition of the physical object or area, in response to the recognized activity being classified as a cleaning activity.
This invention relates to a cleanliness monitoring system designed to assess and update the cleanliness of a physical object or area based on detected activities. The system addresses the challenge of accurately tracking cleanliness levels in environments where manual monitoring is impractical or inefficient. The system includes sensors to detect activities near the object or area and processing circuitry to classify these activities. When an activity is classified as a cleaning activity, the system adjusts the cleanliness estimate in a direction indicating improved cleanliness. This adjustment ensures that the cleanliness estimate reflects the positive impact of the detected cleaning activity. The system may also incorporate additional features, such as adjusting the cleanliness estimate based on the type or duration of the cleaning activity, or using historical data to refine the classification of activities. The goal is to provide a dynamic and automated way to monitor cleanliness, reducing the need for manual inspections and improving accuracy in environments like hospitals, laboratories, or manufacturing facilities.
13. The cleanliness monitoring system of claim 12, wherein the processing circuitry is configured to change the value of the cleanliness estimate in a direction that corresponds to a cleaner condition in joint dependence on the recognized activity being classified as a cleaning activity and on receiving or detecting a verification of the classification.
The cleanliness monitoring system is designed for environments where maintaining cleanliness is critical, such as healthcare facilities, food processing plants, or laboratories. The system addresses the challenge of accurately assessing cleanliness levels by dynamically adjusting cleanliness estimates based on detected activities and verification inputs. The system includes sensors to monitor environmental conditions and activities, as well as processing circuitry that analyzes the data. When an activity is recognized and classified as a cleaning activity, the system adjusts the cleanliness estimate to reflect an improvement. However, this adjustment is only made if the classification is verified, either through user input or additional sensor data. This dual-condition approach ensures that false positives do not skew the cleanliness assessment. The system may also include user interfaces for manual verification or additional sensors to cross-check activity classifications. By requiring both activity recognition and verification, the system provides a more reliable and accurate cleanliness monitoring solution.
16. The method of claim 15, wherein outputting the indication of the value of the cleanliness estimate comprises outputting the indication of the value of the cleanliness estimate as video overlay information, for overlaying a video or still image of the physical object or area.
This invention relates to systems for assessing and displaying cleanliness levels of physical objects or areas, particularly in environments where contamination monitoring is critical, such as healthcare, food processing, or manufacturing. The problem addressed is the need for real-time, visually intuitive cleanliness feedback to ensure proper sanitation practices. The method involves capturing data from one or more sensors, such as cameras or chemical detectors, to analyze the cleanliness of a target object or area. The system processes this data to generate a cleanliness estimate, which quantifies the presence of contaminants like dirt, bacteria, or chemical residues. The key innovation is the way this estimate is presented: the value is overlaid as visual information directly onto a live video feed or still image of the inspected object or area. This overlay can include numerical values, color-coded indicators, or graphical markers that highlight specific contaminated regions. The display ensures users can immediately see which areas require attention without needing separate reports or alerts. The system may also adjust the overlay's transparency or position to avoid obstructing critical visual details. This approach enhances situational awareness and efficiency in cleanliness verification processes.
17. The method of claim 16, wherein the video overlay information comprises a color-coded graphical overlay, wherein the color of the color-coded graphical overlay indicates the value of the cleanliness estimate and wherein the method includes changing the color of the color-coded graphical overlay responsive to changing the value of the cleanliness estimate.
This invention relates to a system for monitoring and visually indicating the cleanliness of a surface, particularly in industrial or medical environments where contamination control is critical. The system addresses the challenge of providing real-time, intuitive feedback on surface cleanliness to users, ensuring compliance with hygiene standards without requiring manual inspection or complex data interpretation. The method involves capturing an image of a surface using a camera or imaging device, then analyzing the image to generate a cleanliness estimate based on detected contaminants, stains, or other visual indicators of dirt or residue. The cleanliness estimate is converted into a color-coded graphical overlay that is superimposed onto the captured image or displayed separately. The color of the overlay corresponds to the cleanliness value, with predefined color gradients representing different levels of contamination—e.g., green for clean, yellow for moderate contamination, and red for heavily soiled surfaces. As the cleanliness estimate changes due to cleaning or further contamination, the color of the overlay dynamically updates to reflect the new value, providing immediate visual feedback. The system may also include additional features such as threshold alerts, historical tracking, or integration with cleaning protocols to guide users in maintaining hygiene standards. The color-coded overlay ensures that even untrained personnel can quickly assess cleanliness without interpreting numerical data, improving efficiency and accuracy in contamination control.
18. The method of claim 15, wherein the method includes the computer system receiving the video images and performing the video analysis to obtain the processed data.
A system and method for analyzing video images to extract processed data involves a computer system that receives video images and performs video analysis to obtain the processed data. The video analysis may include detecting objects, tracking motion, recognizing patterns, or identifying specific features within the video frames. The processed data can be used for various applications, such as surveillance, automation, or decision-making processes. The computer system may employ machine learning algorithms, computer vision techniques, or other analytical methods to process the video images. The system ensures accurate and efficient extraction of relevant information from the video data, enabling real-time or batch processing depending on the application requirements. The method may also include preprocessing steps to enhance image quality, such as noise reduction, contrast adjustment, or frame stabilization, before performing the analysis. The processed data can be stored, transmitted, or used to trigger further actions based on predefined criteria. This approach improves the reliability and effectiveness of video-based monitoring and analysis systems.
19. The method of claim 15, wherein the method includes the computer system receiving the processed data from an associated video analytics system that receives the video images and performs the video analysis.
This invention relates to a computer-implemented method for processing video data to detect and analyze events within a monitored environment. The method addresses the challenge of efficiently extracting meaningful insights from video feeds by integrating video analytics systems to automate the detection and classification of events. The computer system receives processed data from an associated video analytics system, which captures video images and performs real-time analysis to identify relevant events. The video analytics system processes the raw video data to detect motion, object recognition, or other predefined criteria, then generates structured data representing these events. This processed data is transmitted to the computer system, which further analyzes the information to generate actionable insights, such as alerts, reports, or automated responses. The integration of the video analytics system with the computer system ensures that the video data is pre-processed to reduce computational overhead and improve accuracy in event detection. The method enhances surveillance, security, and monitoring applications by automating the analysis of video feeds and providing timely, structured data for decision-making.
20. The method of claim 15, wherein, for changing the value of the cleanliness estimate according to the classification, the method comprises changing the value of the cleanliness estimate in a direction that corresponds to a dirtier condition of the physical object or area, in response to the recognized activity being classified as a dirtying activity.
This invention relates to systems for estimating the cleanliness of physical objects or areas by analyzing activity recognition data. The problem addressed is the need to dynamically adjust cleanliness estimates based on detected activities that may affect cleanliness, such as dirtying or cleaning actions. The method involves monitoring activities in a physical space using sensors or cameras to capture data. An activity recognition system processes this data to classify activities as either dirtying (e.g., spilling, handling dirty objects) or cleaning (e.g., wiping, washing). The cleanliness estimate of the object or area is then adjusted based on the classification. If a dirtying activity is detected, the cleanliness estimate is decreased, indicating a dirtier condition. Conversely, if a cleaning activity is detected, the cleanliness estimate is increased, indicating improved cleanliness. The system may also incorporate additional factors, such as time since the last cleaning or environmental conditions, to refine the estimate. The method ensures that cleanliness assessments remain accurate and up-to-date by dynamically responding to real-world activities that impact cleanliness. This is particularly useful in environments where cleanliness is critical, such as healthcare facilities, food preparation areas, or industrial settings. The system may be integrated into automated cleaning robots, monitoring systems, or maintenance scheduling tools to optimize cleaning operations.
21. The method of claim 15, wherein, for changing the value of the cleanliness estimate according to the classification, the method comprises changing the value of the cleanliness estimate in a direction that corresponds to a cleaner condition of the physical object or area, in response to the recognized activity being classified as a cleaning activity.
This invention relates to systems and methods for estimating the cleanliness of a physical object or area by analyzing recognized activities. The technology addresses the challenge of accurately assessing cleanliness in environments where human or robotic activities may affect cleanliness levels. The method involves monitoring activities within a monitored space, recognizing these activities, and classifying them to determine their impact on cleanliness. When an activity is classified as a cleaning activity, the cleanliness estimate is adjusted in a direction that indicates an improvement in cleanliness. This adjustment reflects the positive effect of the cleaning activity on the physical object or area. The system may use sensors, cameras, or other monitoring devices to detect activities and machine learning models to classify them. The cleanliness estimate is dynamically updated based on the recognized and classified activities, providing real-time feedback on the cleanliness state. This approach enhances the accuracy of cleanliness monitoring by accounting for the specific actions that contribute to or detract from cleanliness. The method can be applied in various settings, including homes, hospitals, and industrial facilities, to maintain hygiene standards and optimize cleaning efforts.
22. The method of claim 15, wherein, for changing the value of the cleanliness estimate according to the classification, the method comprises changing the value of the cleanliness estimate in a direction that corresponds to a cleaner condition of the physical object or area, in response both to the recognized activity being classified as a cleaning activity and receiving or detecting verification of the classification.
This invention relates to systems for estimating the cleanliness of physical objects or areas by analyzing activity data. The problem addressed is the need for accurate and reliable cleanliness assessments, particularly in environments where manual verification is impractical or time-consuming. The invention improves upon prior methods by dynamically adjusting cleanliness estimates based on both automated activity recognition and subsequent verification of those activities. The method involves monitoring activities in a given area or on a physical object to detect potential cleaning actions. When an activity is recognized as a cleaning activity, the system initially classifies it as such. However, the cleanliness estimate is only updated if the classification is verified—either through user input, sensor feedback, or another confirmation mechanism. This verification step ensures that false positives (e.g., misclassified activities) do not inaccurately improve the cleanliness estimate. The adjustment to the cleanliness value is made in a direction that reflects a cleaner condition, but only after both the initial classification and verification are confirmed. This two-step process enhances the reliability of cleanliness tracking in automated systems. The method may be applied in smart home environments, industrial settings, or healthcare facilities where cleanliness monitoring is critical.
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April 28, 2021
May 14, 2024
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